Project Objectives
- Develop an integrated hardware–software platform for automated welfare assessment.
- Combine 3D gait analysis, grimace scoring and behavioural motif analysis.
- Generate robust training datasets across multiple collaborating laboratories.
- Benchmark automated methods against standard cageside assessments.
- Produce an open‑source system transferable across research institutions.
3Rs Impact
- Enhances refinement through sensitive, unbiased detection of pain and distress.
- Reduces animal numbers by increasing statistical power.
- Supports evidence‑based analgesia and post‑operative care.
- Enables early detection of welfare decline.
- Establishes standardized, transferable welfare‑monitoring workflows.
Background
Monitoring pain and well‑being in laboratory mice is crucial for ethical research and scientific accuracy, yet existing approaches are often limited. Traditional cageside assessments rely on manual observation, are vulnerable to bias, and frequently miss subtle signs of discomfort, especially as mice naturally mask pain and distress.
Recent machine‑learning and pose‑estimation tools now allow automated detection of gait changes, facial expressions and sub‑second behavioural motifs. This project integrates these advances into a single homecage‑like chamber containing infrared cameras, 3D tracking, automated grimace scoring, and deep behavioural profiling. The system quantifies posture, gait, ethological behaviours and behavioural flow with unprecedented detail.
By producing standardized and objective well‑being assessments, this system addresses major gaps in reproducibility, laboratory‑to‑laboratory comparability, and early detection of welfare‑relevant phenotypes. The platform aims to support evidence‑based analgesia protocols, improve humane endpoints, and ultimately raise welfare standards across biomedical research.
